{"id":44282,"date":"2021-11-24T12:46:52","date_gmt":"2021-11-24T20:46:52","guid":{"rendered":"https:\/\/sites.evergreen.edu\/mesweekly\/?p=44282"},"modified":"2021-11-24T13:52:31","modified_gmt":"2021-11-24T21:52:31","slug":"it-data-management-journey-image-gis-analyst-permanent-olympia-wa","status":"publish","type":"post","link":"https:\/\/sites.evergreen.edu\/mesweekly\/it-data-management-journey-image-gis-analyst-permanent-olympia-wa\/","title":{"rendered":"Job: IT Data Management – Journey (Image & GIS Analyst) – Permanent (Olympia, WA)"},"content":{"rendered":"

For more information, follow this link:<\/strong> State of Washington Job Opportunities | Work that Matters (governmentjobs.com)<\/a><\/p>\n

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Salary – <\/strong>$77,544.00 – $101,748.00 Annually<\/div>\n
.<\/span><\/div>\n
\n

\u00a0Tasks include:<\/strong><\/p>\n

    \n
  • Evaluating and determining project requirements and business needs to implement the most-appropriate and best-available analysis\/modeling methods and tools.<\/li>\n
  • Translating and integrating resource data (from a wide variety of sources, formats, and quality) into analysis workflows and modeling methods.<\/li>\n
  • Using spatial statistics and geospatial analyses (generally with Python, R code or ESRI software tools) to generate modeled,\u00a0\u201cvalue-added\u201d\u00a0data products from raw\/base resource data.<\/li>\n
  • Developing, using, and maintaining scripts in Python and R to create automated workflows for improving efficiency and repeatability of analysis results \u2013 supporting the re-use of code and scripts by standardizing and maintaining in a code repository.<\/li>\n
  • Performing validation and quality control on analysis methods and modeled data products to ensure accuracy, integrity, and reliability of results.<\/li>\n
  • Maintaining a modeled data repository for the Wildlife Program and catalogs data in this repository.<\/li>\n
  • Distributing modeled data as local feature classes and web services for use by WDFW staff and external customers.<\/li>\n
  • Supporting the development of tools, applications and tools, interfaces (using ESRI COTS software or custom applications in JavaScript or .NET) for the display, query, and extraction of modeled data products.<\/li>\n<\/ul>\n

    Performs Image Analysis: Develops, interprets and maintains remotely sensed image data (from satellite, aerial, UAV, camera trap imagery).<\/strong><\/p>\n

    \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Tasks include:<\/strong><\/p>\n

      \n
    • Supporting WDFW field data collection, data management and processing of imagery via UAV (drones) or passive sensors (e.g., camera traps).<\/li>\n
    • Conducting quality assurance on remotely sensed, image data collection and processing.<\/li>\n
    • Translating, integrating and managing remotely sensed data (multi-spectral images, Lidar) often comprised of disparate resolutions, formats, spatial extents, spatial\/spectral integrity, quality and completeness.<\/li>\n
    • Conducting spectral and object-orientated image classification using software such as ArcGIS, Imagine and eCognition.<\/li>\n<\/ul>\n

      Provides general GIS and IT support to Wildlife Program staff.<\/strong><\/p>\n

      \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Tasks include:<\/strong><\/p>\n

        \n
      • Supporting requests for modeled data products, classified imagery and other resource data that is managed by the Wildlife program.<\/li>\n
      • Supporting the use of ESRI GIS Desktop software, especially raster and geo-processing tools.<\/li>\n
      • Coordinating with other GIS staff on developing, maintaining, and publishing instructions and guides for GIS software and applications.<\/li>\n
      • Supporting the use of Image-processing software.<\/li>\n
      • Supporting requests for ESRI-created maps and webmaps.<\/li>\n
      • Assisting with troubleshooting and resolving bugs\/issues with GIS and Image-Classification software.<\/li>\n<\/ul>\n

        Advises and coordinates with other IT\/GIS staff on data and technology standards, methods, and policies.<\/strong><\/p>\n

        \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Tasks include:<\/strong><\/p>\n

          \n
        • Consulting with IT staff and IT managers and participates in committees to establish data governance, data storage\/organization requirements, data distribution and visualization methods.<\/li>\n
        • Testing and evaluating new and emerging GIS and remote-sensing technologies for appropriate use in Wildlife technology stacks.<\/li>\n
        • Monitoring and evaluating advancements in GIS and image data and processes for use in advanced wildlife analysis and modeling applications.<\/li>\n<\/ul>\n

          WORKING CONDITIONS:<\/strong><\/p>\n

            \n
          • Work Setting, including hazards: \u00a0 \u00a0<\/strong>\n
              \n
            1. Work is performed in an office setting – requires extensive computer use and sitting.<\/li>\n<\/ol>\n<\/li>\n
            2. Schedule: \u00a0\u00a0<\/strong>\n
                \n
              1. Typically, work schedule is 8:00 am – 5:00 pm Monday through Friday \u2013 requires flexibility in work schedule to respond to dynamic project requirements and priorities.<\/li>\n<\/ol>\n<\/li>\n
              2. Travel Requirements:\u00a0<\/strong>\n
                  \n
                1. Some travel is required to participate in training, field work and professional conferences.<\/li>\n<\/ol>\n<\/li>\n
                2. Tools and Equipment:\u00a0<\/strong>\n
                    \n
                  1. Computer hardware and software with emphasis on geographic information systems, remote sensing and image analysis, enterprise relational database management systems, mobile technology, and data collection platforms.<\/li>\n<\/ol>\n<\/li>\n
                  2. Customer Interactions:<\/strong>\n
                      \n
                    1. Successful delivery of data analysis and enterprise data management solutions \u2013 effective interpersonal communication skills, as well as a strong aptitude for interdisciplinary collaboration, consultation, and teamwork.<\/li>\n<\/ol>\n<\/li>\n<\/ul>\n

                      Qualifications<\/p>\n

                      REQUIRED QUALIFICATIONS:<\/strong><\/p>\n

                      \n
                        \n
                      • Bachelor\u2019s degree from an accredited college or university with major course work in Geographic Information Systems, Data Science, Remote Sensing, Landscape Ecology, Geography, or a closely related field.<\/li>\n<\/ul>\n<\/div>\n

                        AND<\/strong><\/p>\n

                        \n
                          \n
                        • Five (5) years of professional GIS and data management experience, using ESRI ArcGIS product suite or similar GIS software and using scripting languages such as Python or R.<\/li>\n<\/ul>\n<\/div>\n

                          Knowledge of:<\/strong><\/p>\n

                            \n
                          • Spatial statistics and experience with modeling wildlife species\/habitat data (e.g., resource selection, spatial distribution patterns, habitat suitability modeling, home range analysis, etc.).<\/li>\n
                          • Complex landscape ecology principles and ability to translate this understanding into valid models, using spatial data and remotely sensed imagery.<\/li>\n
                          • Methods and techniques related to collecting, managing, and analyzing imagery and other spatial data.<\/li>\n
                          • Principles of computer programming logic as they relate to Geographic Information Systems (GIS) data processing and automation.<\/li>\n
                          • Current technology and industry trends with respect to GIS and Image-classification software, cloud computing, mobile solutions.<\/li>\n
                          • Principles and best practices of data and database design, development, and maintenance.<\/li>\n
                          • Maintaining modeled and image data and associated metadata documentation in a data repository.<\/li>\n<\/ul>\n

                            Ability to:<\/strong><\/p>\n

                              \n
                            • Independently design and execute complex geospatial and image analysis workflows to consistently achieve successful, reliable, and effective data-driven outcomes.<\/li>\n
                            • Write and maintain code, using Python or R, to automate tasks and manage data across systems and platforms.<\/li>\n
                            • Identify, utilize, and customize CotS applications, such as ESRI\u2019s webmaps and dashboards, for displaying and querying modeled or image-classified data.<\/li>\n
                            • Conduct advanced spatial statistical modeling and assess validity of results using appropriate statistical methods and packages.<\/li>\n
                            • Process and classify image data using appropriate methods and software.<\/li>\n<\/ul>\n

                              Certifications\/Licenses:\u00a0<\/strong><\/p>\n

                              \n
                                \n
                              • Valid Driver\u2019s License.\u00a0<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":9433,"featured_media":34097,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_s2mail":"yes"},"categories":[15],"tags":[4,28,33,141,13],"_links":{"self":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/44282"}],"collection":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/users\/9433"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/comments?post=44282"}],"version-history":[{"count":4,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/44282\/revisions"}],"predecessor-version":[{"id":44305,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/44282\/revisions\/44305"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media\/34097"}],"wp:attachment":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media?parent=44282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/categories?post=44282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/tags?post=44282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}